公开(公告)号：US20160034814A1

公开(公告)日：2016-02-04

申请号：US14816999

申请日：2015-08-03

申请人： Kartik Audhkhasi ,  Osonde Osoba ,  Bart Kosko

发明人： Kartik Audhkhasi ,  Osonde Osoba ,  Bart Kosko

IPC分类号： G06N3/08 ,  G06N99/00 ,  G06N3/04

CPC分类号： G06N3/08

摘要： A learning computer system may update parameters and states of an uncertain system. The system may receive data from a user or other source; process the received data through layers of processing units, thereby generating processed data; process the processed data to produce one or more intermediate or output signals; compare the one or more intermediate or output signals with one or more reference signals to generate information indicative of a performance measure of one or more of the layers of processing units; send information indicative of the performance measure back through the layers of processing units; process the information indicative of the performance measure in the processing units and in interconnections between the processing units; generate random, chaotic, fuzzy, or other numerical perturbations of the received data, the processed data, or the one or more intermediate or output signals; update the parameters and states of the uncertain system using the received data, the numerical perturbations, and previous parameters and states of the uncertain system; determine whether the generated numerical perturbations satisfy a condition; and if the numerical perturbations satisfy the condition, inject the numerical perturbations into one or more of the parameters or states, the received data, the processed data, or one or more of the processing units.

摘要翻译： 学习计算机系统可以更新不确定系统的参数和状态。 系统可以从用户或其他来源接收数据; 通过处理单元层处理接收到的数据，从而生成处理的数据; 处理经处理的数据以产生一个或多个中间或输出信号; 将一个或多个中间或输出信号与一个或多个参考信号进行比较以产生指示处理单元的一个或多个层的性能测量的信息; 通过处理单元的层发送指示性能测量的信息; 处理指示处理单元中的性能测量的信息以及处理单元之间的互连; 产生接收数据，处理数据或一个或多个中间或输出信号的随机，混沌，模糊或其他数字扰动; 使用接收到的数据，数值扰动和不确定系统的先前参数和状态来更新不确定系统的参数和状态; 确定所产生的数字扰动是否满足条件; 并且如果数字扰动满足条件，则将数字扰动注入一个或多个参数或状态，接收的数据，处理的数据或一个或多个处理单元。

公开(公告)号：US20160005399A1

公开(公告)日：2016-01-07

申请号：US14802760

申请日：2015-07-17

申请人： Kartik Audhkhasi ,  Osonde Osoba ,  Bart Kosko

发明人： Kartik Audhkhasi ,  Osonde Osoba ,  Bart Kosko

IPC分类号： G10L15/14 ,  G10L25/33 ,  G10L25/36 ,  G10L15/06

CPC分类号： G10L15/144 ,  G10L15/063 ,  G10L25/33 ,  G10L25/36

摘要： A learning computer system may estimate unknown parameters and states of a stochastic or uncertain system having a probability structure. The system may include a data processing system that may include a hardware processor that has a configuration that: receives data; generates random, chaotic, fuzzy, or other numerical perturbations of the data, one or more of the states, or the probability structure; estimates observed and hidden states of the stochastic or uncertain system using the data, the generated perturbations, previous states of the stochastic or uncertain system, or estimated states of the stochastic or uncertain system; and causes perturbations or independent noise to be injected into the data, the states, or the stochastic or uncertain system so as to speed up training or learning of the probability structure and of the system parameters or the states.

摘要翻译： 学习计算机系统可以估计具有概率结构的随机或不确定系统的未知参数和状态。 该系统可以包括数据处理系统，其可以包括具有以下配置的硬件处理器：接收数据; 产生数据的随机，混乱，模糊或其他数字扰动，一个或多个状态或概率结构; 使用数据，生成的扰动，随机或不确定系统的先前状态或随机或不确定系统的估计状态的随机或不确定系统的观测和隐藏状态的估计; 并引起扰动或独立噪声注入到数据，状态或随机或不确定系统中，以加速对概率结构和系统参数或状态的训练或学习。

公开(公告)号：US20160019459A1

公开(公告)日：2016-01-21

申请号：US14803797

申请日：2015-07-20

申请人： Kartik Audhkhasi ,  Bart Kosko ,  Osonde Osoba

发明人： Kartik Audhkhasi ,  Bart Kosko ,  Osonde Osoba

IPC分类号： G06N3/08 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06K9/6217 ,  G06K9/6255 ,  G06K9/66 ,  G06N3/04 ,  G06N3/0454 ,  G06N3/084 ,  G06N7/005

摘要： A learning computer system may include a data processing system and a hardware processor and may estimate parameters and states of a stochastic or uncertain system. The system may receive data from a user or other source; process the received data through layers of processing units, thereby generating processed data; apply masks or filters to the processed data using convolutional processing; process the masked or filtered data to produce one or more intermediate and output signals; compare the output signals with reference signals to generate error signals; send and process the error signals back through the layers of processing units; generate random, chaotic, fuzzy, or other numerical perturbations of the received data, the processed data, or the output signals; estimate the parameters and states of the stochastic or uncertain system using the received data, the numerical perturbations, and previous parameters and states of the stochastic or uncertain system; determine whether the generated numerical perturbations satisfy a condition; and, if the numerical perturbations satisfy the condition, inject the numerical perturbations into the estimated parameters or states, the received data, the processed data, the masked or filtered data, or the processing units.

摘要翻译： 学习计算机系统可以包括数据处理系统和硬件处理器，并且可以估计随机或不确定系统的参数和状态。 系统可以从用户或其他来源接收数据; 通过处理单元层处理接收到的数据，从而生成处理的数据; 使用卷积处理对已处理数据应用掩码或过滤器; 处理屏蔽或滤波的数据以产生一个或多个中间和输出信号; 将输出信号与参考信号进行比较，产生误差信号; 通过处理单元的层发送和处理错误信号; 产生接收数据，处理数据或输出信号的随机，混沌，模糊或其他数字扰动; 使用接收数据，数值扰动以及随机或不确定系统的先前参数和状态来估计随机或不确定系统的参数和状态; 确定所产生的数字扰动是否满足条件; 并且如果数值扰动满足条件，则将数值扰动注入估计的参数或状态，接收的数据，处理的数据，被掩蔽的或被滤波的数据或处理单元。

公开(公告)号：US20110040554A1

公开(公告)日：2011-02-17

申请号：US12541927

申请日：2009-08-15

申请人： Kartik Audhkhasi ,  Om D. Deshmukh ,  Kundan Kandhway ,  Ashish Verma

发明人： Kartik Audhkhasi ,  Om D. Deshmukh ,  Kundan Kandhway ,  Ashish Verma

IPC分类号： G06F17/27 ,  G10L15/26 ,  G10L13/08

CPC分类号： G10L15/26 ,  G09B19/04

摘要： A procedure to automatically evaluate the spoken fluency of a speaker by prompting the speaker to talk on a given topic, recording the speaker's speech to get a recorded sample of speech, and then analyzing the patterns of disfluencies in the speech to compute a numerical score to quantify the spoken fluency skills of the speakers. The numerical fluency score accounts for various prosodic and lexical features, including formant-based filled-pause detection, closely-occurring exact and inexact repeat N-grams, normalized average distance between consecutive occurrences of N-grams. The lexical features and prosodic features are combined to classify the speaker with a C-class classification and develop a rating for the speaker.

摘要翻译： 一个程序，通过提示说话者在给定的主题上进行谈话，记录讲话者的语音以获得记录的语音样本，然后分析语音中的不清楚的模式以计算数字得分，自动评估讲话者的口语流畅性 量化演讲者的口语流利能力。 数值流利度分数考虑到各种韵律和词汇特征，包括基于共振峰的填充暂停检测，紧密发生的精确和不精确的重复N克，连续出现的N克之间的归一化平均距离。 词汇特征和韵律特征相结合，将扬声器分类为C级分类，并为扬声器开发评级。

公开(公告)号：US08457967B2

公开(公告)日：2013-06-04

申请号：US12541927

申请日：2009-08-15

申请人： Kartik Audhkhasi ,  Om D. Deshmukh ,  Kundan Kandhway ,  Ashish Verma

发明人： Kartik Audhkhasi ,  Om D. Deshmukh ,  Kundan Kandhway ,  Ashish Verma

IPC分类号： G10L15/04 ,  G10L15/26 ,  G10L15/06 ,  G10L13/00 ,  G10L21/00 ,  G06F17/27

CPC分类号： G10L15/26 ,  G09B19/04

摘要： A procedure to automatically evaluate the spoken fluency of a speaker by prompting the speaker to talk on a given topic, recording the speaker's speech to get a recorded sample of speech, and then analyzing the patterns of disfluencies in the speech to compute a numerical score to quantify the spoken fluency skills of the speakers. The numerical fluency score accounts for various prosodic and lexical features, including formant-based filled-pause detection, closely-occurring exact and inexact repeat N-grams, normalized average distance between consecutive occurrences of N-grams. The lexical features and prosodic features are combined to classify the speaker with a C-class classification and develop a rating for the speaker.

摘要翻译： 一个程序，通过提示说话者在给定的主题上进行谈话，记录讲话者的语音以获得记录的语音样本，然后分析语音中的不清楚的模式以计算数字得分，自动评估讲话者的口语流畅性 量化演讲者的口语流利能力。 数值流利度分数考虑到各种韵律和词汇特征，包括基于共振峰的填充暂停检测，紧密发生的精确和不精确的重复N克，连续出现的N克之间的归一化平均距离。 词汇特征和韵律特征相结合，将扬声器分类为C级分类，并为扬声器开发评级。